in order to evaluate capability of the landsat-etm and irs-p6-liss iv images for canopy cover mapping a case study was done on the forests of javanroud in kermanshah province. after evaluation of the geometric and radiometric quality of the data, the etm+ images, the etm+ images were geometrically corrected with gcps and the images were registered with rmse error 0.46 and 0.48 pixels, for x and...

This study demonstrates the ability of GIS and Remote Sensing in capturing spatial-temporal data on land use and land cover classes. The nine land cover classes captured were Built-up area, Secondary forests, Savannah, Grasslands, and Shrublands containing herbaceous, Rain-fed shrub crops, Fresh water swamps, Water bodies, and Farmlands. The remote sensed imageries also displayed how the land u...

in order to study the effect of elevation on quantitative and qualitative characteristics of the humid forests of guilan shafaroud, series 17, 16 and 7 were selected that fall in to three height classes; class 1 (‏less than 500 m), class 2 (‏500 – 1000 m) and class 3 (‏1000 – 1600 m). in height class 1, 2 and 3 sample plots were determined as 4, 15 and 20 respectively and each sample plot was 0...

Land cover of Finnish Lapland was classified to 16 land cover classes using optical IRS LISS, Spot XS and MODIS satellite images, ancillary GIS data and decision tree classifier. The aim of this study was to test decision tree classifier for land cover classification and study the effects of its parameters to classification result. In the best case, the overall accuracy was about 68% for all 16...

The land cover classes developed under the coordination of the International Geosphere-Biosphere Programme Data and Information System (IGBP-DIS) have been analyzed for a study area that includes the Conterminous United States and portions of Mexico and Canada. The 1-km resolution data have been analyzed to produce a gridded data set that includes within each 20-km grid cell: 1) the three most ...

Landsat Thematic Mapper (TM) data have been extensively used for land cover classification, but Terra ASTER and SPOT High Resolution Geometric (HRG) data applications are just beginning. This paper compares the capabilities of TM, ASTER, and HRG in land cover classification in the Amazon basin. Maximum likelihood classification was used for selected multi-sensor image classification. This resea...

Land cover/land use categories are relevant components in land management. Understanding how land cover/land use change over time is necessary to assess the consequences of humans and natural stressors on the earth’s environment and resources. The aim of the study was to map and monitor the spatial and temporal change in land cover/land use for the periods of 1977, 1991 and 2016 and to predict ...

Quantitatively modeling the spatial distribution and uncertainties of landcover classes is crucial in geographic information science. However, currently suitable methods for modeling multinomial categorical variables for geographical analyses are rare because of the complex spatial interdependence of multinomial classes. In this paper we use a recently presented two-dimensional Markov chain mod...